I'm Ariel Menezes.

TL;DR: research is fun; federated learning, edge computing and privacy in our algorithms sounds like interesting and important topics; so this is the next step in my long term personal development plan.

This is where I delved deeper into the world of programming. I engaged in a variety of Machine Learning projects and publications, covering diverse topics such as classification, object detection, recognition, and beyond. Additionally, during my free time, I dedicated myself to studying and enrolling in various courses across multiple domains.

This was where I started my programming journey. I learned a little bit of C and Portugol in the first and second semester, then a little bit of MATLAB, robotics, and microcontrollers. I also learned about electronics, power systems, and more. At some point in the middle of the course, I started learning Python and doing little projects with it: from web scraping to desktop applications, and even Machine Learning. During my final two semesters I worked on my Bachelor's Degree Final Project: I developed a Machine Learning project using a custom dataset of panoramic dental radiographies. I worked on this project from data collection to training and testing a Convolutional Neural Network for classification, from zero. That's when I realized my true passion for software development.

As a Software Engineer at IBM, I specialize in developing and maintaining enterprise-grade applications using Java, Spring Boot, Angular, and Node.js. My role involves creating scalable and efficient solutions that meet complex business needs.

Projects and publications in Machine Learning, spanning classification, object detection, recognition, and more. Teaching assistant in Data Structures and Algorithms.